Low bit rate voice coding can provide very efficient communications capability for such applications as voice mail, secure telephony, integrated voice and data transmission over packet networks, and narrow band cellular radio. Code excited linear prediction (CELP) is a coding method that offers robust, intelligible, good quality speech at low bit rates, e.g., 4.8 to 16 kilobits per second. Although based on the principles of linear predictive coding (LPC), CELP uses analysis-by-synthesis vector quantization to match the input speech, rather than imposing any strict excitation model. As a result, CELP sounds less mechanical than traditional CELP coders, and it is more robust to non-speech sounds and environmental noise. CELP has been shown to provide a high degree of speaker identifiability as well.
Because the excitation is determined through an exhaustive analysis-by-synthesis vector quantization approach, the CELP method is computationally complex. A backward gain adaptation is typically performed in CELP coders to scale the amplitude of the codebook vectors (codevectors) to the input speech based on previous gain values. Such adaptation is carried out at both ends of the communication. However, the accuracy of the adaptation process has not been sufficient to meet requirements specified for the interoperability of fixed-point CELP encoders with floating-point CELP decoders and vice versa.
In view of the foregoing, improvements are needed in both the accuracy and computational complexity of CELP coders.